Computational Phenomenology of Temporal Experience in Autism: Quantifying the Emotional and Narrative Characteristics of Lived Unpredictability
Kacper Dudzic, Karolina Dro\.zd\.z, Maciej Wodzi\'nski, Anastazja Szu{\l}a, Marcin Moskalewicz

TL;DR
This study combines phenomenological interviews and computational analysis to quantify how unpredictability in lived experience affects autistic individuals' narratives and emotional expression, revealing core temporal challenges.
Contribution
It introduces an integrated methodology bridging phenomenological and computational approaches to study temporal experience in autism, overcoming previous research limitations.
Findings
Autistic individuals experience significant unpredictability in temporality.
Autistic narratives show more negative emotional valence, especially in immediacy and suddenness.
Autistic autobiographies resemble real-life stories more than imaginary ones.
Abstract
Disturbances in temporality, such as desynchronization with the social environment and its unpredictability, are considered core features of autism with a deep impact on relationships. However, limitations regarding research on this issue include: 1) the dominance of deficit-based medical models of autism, 2) sample size in qualitative research, and 3) the lack of phenomenological anchoring in computational research. To bridge the gap between phenomenological and computational approaches and overcome sample-size limitations, our research integrated three methodologies. Study A: structured phenomenological interviews with autistic individuals using the Transdiagnostic Assessment of Temporal Experience. Study B: computational analysis of an autobiographical corpus of autistic narratives built for this purpose. Study C: a replication of a computational study using narrative flow measures…
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Taxonomy
TopicsAutism Spectrum Disorder Research · Identity, Memory, and Therapy · Memory and Neural Mechanisms
